Online Media Monitoring for Water and Development

Using online media and user generated content for water management and food security. People share. We listen.

Real-time monitoring

FloodTags monitors online media data in real-time, to detect new events and get immediate from-the-ground coverage. Effective for flood monitoring and response like at the Red Cross Operation Centre in Manilla.

Floods & Disasters

We started with flood management and this is still the anchor of the company. Building on this experience, the software we applied on floods now forms the example for various other water management applications.

Who we are

FloodTags analyses online media and user generated content for water management and food security. Data sources include online news articles, blogs, forums, Twitter, Facebook public pages, and we connect to messengers such as WhatsApp and Telegram. We analyse these sources by using a mix of artificial intelligence, natural language processing and combinations with external data sources, including satellite imagery. Applications comprise real-time and historic (trend) analysis for emergency flood response, water scarcity management, water conflict resolution, integrated water management, food security and other water- and development related applications.

FloodTags believes that citizens and local communities are key resources in any social and water management problem. By listening to and anticipating on local perspectives, decision makers can take supported measures and responders have direct insight in the assistance needed on-the-ground.

Collect Online Media

Citizens and journalists describe new water crises in thousands of online messages. FloodTags collects their observations from Social Media, Blogs, Forums, Online News

Filter and Enrich

FloodTags and partners analyse the data using a mix of natural language processing and hydro-meteorologic enrichment, including remote sensed data

Share to Client

The Information is shared as a Service (IaaS) via a website and API that connects to client-side software. Applications include an array of water applications.

Collaborate with us

Floodtags has a partner network of top universities and institutions, with whom we improve the filters & enrichment algorithms for a wide range of use cases. Among our partners are Deltares, Radboud University Nijmegen, VU Amsterdam, Delft University of Technology and NASA. If you are a reseacher, anywhere in the world, working on social media for development: Feel welcome to contact us!

BARCELONA (Thomson Reuters Foundation) - Spontaneous tweets about major floods are being turned into a mapping tool that could be used by emergency services and disaster response teams to save lives and provide aid, Dutch researchers said. When a crisis strikes, people increasingly find out about it from social media, as individuals and groups take to the internet to spread the word.

After the Indonesian capital Jakarta was hit by floods this February, related tweets peaked at almost 900 a minute, with a significant number including information about location and water depth, according to a joint study by two Dutch organizations, Deltares and Floodtags. Read more

Gaston Nina

Frequently Asked Questions

Yes definitely. Most importantly, the data must be public. If people post something to their friends alone, we cannot use it. If they post it on a public Facebook page from your organisation, we can ingest with little problems.

You are right that Twitter is not as popular in one place as it is in the other. However, we find that in regions with low Twitter counts, people still want to express themselves one way or the other. Besides a few tweets (we have found that there are always some tweets when it floods), there public messages are shared on blogs, forums, public Facebook pages, flickr etc. These sources can be ingested and made available for you. Do check out the blog we wrote about Tanzania, where we connected the software to online news media and to a popular (local) forum called Jamiiforums.

Note that this is discussing the real-time media data, which comes in on very short timescales (within minutes after the start of an event). On a different timescale (within hours after start of an event) much more data becomes available from various news media. These describe the local situation often in great detail.

Indeed online media data is written by people, which makes the data source subjective. To still be able to use it as a trustworthy datasource, together with our scientific partners, we determine the reliability and relevance of the online media content in three steps

By natural language processing (within the message we determine what is says)

By comparing the messages against each other (different independent messages can confirm each other) and

By comparing the messages with other data (messages after rain in low lying areas are often more relevant, than messages shared during a drought on high plains).

We have the precision of the natural language processing alone (without any combinations of data) now fluctuating between 70%-90% dependent of the source (this means that 10%-30% of messages we think are about floods, are actually about something else than floods) with an acceptable recall (number of false negatives, i.e. there are floods but they are not identified by us as floods). With various techniques and data combinations, precision can be increased to near 100%, with the same number of false negatives (some small events may always be missed). Depending on the use-case, we can optimize precision versus recall. For instance Philippine Red Cross has a high tolerance for false positives, but they are much averse to false negatives. Another Client (a museum we work for) has high tolerance for false negatives, but what is shown has to be true (no false positives).

Starting point in The Philippines was that (even without requesting people to report on a new floods) there are a massive amount of photos and observations circulating online. Rather that asking communities to report, we wanted to benefit from what is already out there. And this is the same approach we take in every new implementation: First let’s see what is out there that we can use!

Of course the next step is to engage with the people and the communities directly, and collect even more information. You can specifically request your volunteers or citizens actively to post about the situation they are in and the results would mean an even better understanding of the local situation. This is also what we are preparing now. Building on the information that we receive by passive listening, as FloodTags we deliver the data to:

Target the regions where information is needed most: Regions that have a high risk but very little data coming in (for some regions we get tens of thousands tweets, perhaps not a priority to get even more data from there)

Target the champions in those regions, that are likely to contribute. These can be users that already shared useful information, or users that have shown their public engagement otherwise on those regions.

Totally agree. Actually we need logical thinking people to “teach” the computer which articles (and what parts of it) they find important. If you think your staff could help in this that would be great! Via an interface we deliver (a website), they would need to point out which word is an event is interesting. E.g. the word “flood” between the word “new” and “hits” (making this “new flood hits”) indicates a new flood event, the number “3.000” before “evacuated” means that 3.000 people were evacuated. Etc. And this can become very specific for your organisations’ interest (what do YOU want to know). If your staff could help here that would be fantastic.

Secondly, for the easiness of the uptake, we would like to explore together with the staff on how to show the results of the software. E.g. we can show it in our own Dashboard, but also it could be connected to already running systems in your office (do you already have some kind of dashboard or systems). Similarly. the results of the impact forecasting (what impact could be expected at a given forecast) could be shared through a lookup table, which would make it very non-technical and easy to use without any further server or software requirements. To know the best way to share the results, we request the input of your staff.

FloodTags is a hosted software solution that can be connected to via an API or front-end dashboard under a subscription. We charge separately for Client specific new feature development.

The code itself is shared with our Clients and can freely be used (so you can also choose to host and maintain the resulting software and configuration yourself). We are working on the license to go fully open source.